This directory contains the
rgs3 package for the R software environment.
This package wraps the GS3 program for genomic prediction and selection.
See the web page from Andrés Legarra for more information.
Before installing the
rgs3 package, the latest version of the GS3 program should already be installed on your computer (see on GitHub).
More precisely, the executable should be present in your PATH, under the name
gs3 for Unix-like operating systems (GNU/Linux, Mac OS) and
gs3.exe for Microsoft Windows.
On Unix-like operating systems, you can save the executable in a new directory named
binin your home directory, and then add the path to this new directory to the environment variable
On Windows, you can save the executable in a new directory named
GS3, for instance in
C:\Program Files, and then add the path to this new directory to the environment variable
Configuration parameters -> System -> Advanced, or something similar).
To check if R properly detects the new directory, open a new R session, and call
To check if the executable is found in your PATH, open a new R session, and call
system("gs3.exe") for Windows).
Then, to install the
rgs3 package, the easiest is to download the released
.tar.gz from SourceSup here, open a R session and run the following command:
install.packages("/path/to/rgs3_<version>.tar.gz", repos=NULL, type="source")
You can also install the latest version of the source code directly from GitHub, by opening a R session and running the following commands:
library(devtools) # can be installed from the CRAN install_github("INRA/rgs3", build_vignettes=TRUE)
Note that creating the vignettes may take a couple of minutes.
Once this is done, the
rgs3 package should be available on your computer.
rgs3 package is installed on your computer, it can be loaded into a R session:
library(rgs3) help(package="rgs3") browseVignettes("rgs3")
As a lot of time and effort were spent in creating the GS3 program, please cite it when using it for data analysis:
Legarra, A., Ricard, A., Filangi, O. GS3, a software for genome-wide genetic evaluations and validations. 2014.
You should also cite the
citation() for citing R itself.
When encountering a problem with the package, you can report issues on GitHub directly (here).
Remember to copy-paste the output of
sessionInfo() to help efficiently diagnose the problem and find a solution.
You can contribute in various ways: